The proposed collaboration aims to strengthen the ability of the Capital to identify pollution sources at a granular level, assess their impact, and enable targeted, timely interventions across sectors.
Hyperlocal source apportionment, sensor-based monitoring and real time data are expected be among the highlights of an artificial intelligence (AI)- enabled decision support system (DSS) that is likely to be developed for the Capital as the Delhi government explores a collaboration with Indian Institute of Technology Kanpur to tackle the air pollution in the city.
“Under the leadership of CM Rekha Gupta, we are ensuring that Delhi’s fight against pollution must be scientific, sustained and strategic. We are moving towards a model where decisions are driven by real-time data, source identification and measurable outcomes, not reactive measures,” Environment Minister Manjinder Singh Sirsa was quoted as saying in an official statement on Sunday. The focus, he said, is to move away from blanket restrictions towards targeted action at pollution hotspots.
The proposed collaboration, according to an official statement, aims to strengthen the ability of the Capital to identify pollution sources at a granular level, assess their impact, and enable targeted, timely interventions across sectors.
“A key pillar of this approach is dynamic source apportionment, which will help authorities scientifically identify contributions from dust, transport, industry, biomass burning and regional factors.
This evidence will enable agencies to act at the source of pollution, rather than resorting to blanket bans and reactive measures,” the official statement read.
“Our objective is clear — pollution control cannot be seasonal. Delhi needs a 365-day action framework that combines technology, governance and enforcement, working in complete coordination backed by data driven decision-making,” the Minister added.
At present, the Capital relies on Indian Institute of Tropical Meteorology Pune’s (IITM) DSS. Experts have flagged concerns in the past about the reliability of data. The Indian Express had reported on October 1 that Delhi’s Air Quality Early Warning System (AQEWS) has been able to forecast high-pollution days with more than 80% accuracy, but its reliance on outdated emission inventories and the tendency to underpredict pollutant levels limit its effectiveness, according to a study by the public policy think tank Council on Energy, Environment, and Water (CEEW).
The AQEWS is run by the Indian Institute of Tropical Meteorology (IITM), Pune, and the India Meteorological Department (IMD). It was launched by the Union Ministry of Earth Sciences in 2018 to forecast Delhi’s air quality three days in advance.
In 2021, a Decision Support System (DSS) that tracks sectoral and regional contributions to PM2.5 pollution, was integrated into the system.
According to the study, the ability of AQEWS to detect the most severe episodes of air pollution remains poor, even though improvements have been seen over the past year. “While the AQEWS could only predict 1 out of 15 air pollution episodes with an AQI > 400 in 2023-24, it forecast 5 out of 14 such episodes in 2024-25,” it notes.
Last month, in another report, The Indian Express had highlighted that Delhi’s annual winter response, from dust control to vehicular restrictions, continues to be undertaken without a clear grasp of the sources of pollution in the city. The city’s clean-air action plan has not been updated for seven years, even as a new source-apportionment study was completed in 2023, the National Green Tribunal (NGT) was recently informed.
Meanwhile, the Delhi government on Sunday said it is simultaneously acting on vehicular emissions, road dust, polluting industries and waste management amid the fight against air pollution.
In the last 24 hours, agencies inspected over 340 construction and demolition sites, swept more than 6,000 km of roads and issued over 7,000 vehicular pollution challans.